Özer, Mahmut | Erdem, Rıza | Provaznik, Ivo

Makale | 2004 | NeuroReport15 ( 2 ) , pp.335 - 338

Voltage-gated ion channels are of great importance in the generation and propagation of electrical signals in the excitable cell membranes. How these channels respond to changes in the potential across the membrane has been a challenging problem, and different approaches have been proposed to address the mechanism of voltage sensing and gating in these channels. In this study, we attempt a new approach by considering a simple two-state gate system and applying the path probability method to construct a nonequilibrium statistical mechanical model of the system. The model which is based on the principles of statistical physics provide . . .s a firm physical basis for ion channel gating. © 2004 Lippincott Williams & Wilkins Daha fazlası Daha az

Özer, Mahmut | Uzuntarla, Muhammet | Perc, Matjaž | Graham, Lyle J.

Makale | 2009 | Journal of Theoretical Biology261 ( 1 ) , pp.83 - 92

Özer, Mahmut | Provaznik, Ivo

Makale | 2005 | JOURNAL OF THEORETICAL BIOLOGY233 ( 2 ) , pp.237 - 243

The precise form of the rate constant functions of ion channels is very crucial for reproducing the electrophysiological behavior. Therefore, how well they account for experimental data plays an important role in the behavior of the model. In this study, we derive kinetic coefficients of activation and inactivation gates in ion channels by Onsager reciprocity theorem for an ensemble of gating particles, and propose that the obtained kinetic coefficients can be used as a comparative tool for the empirical validity of fitted rate constant functions to experimental data. We also illustrate its applicability based on the activation and . . .inactivation kinetics of T-type calcium channel in thalamic relay neurons. We show that the shape of the steady-state curve by itself seems to be a poor indicator of the functional form of the rate functions, but the time constant curves reflect considerable variation depending on the particular form of the rate functions, and that the kinetic coefficients related to the time constants provide a powerful tool to determine the empirical validity of the fitted rate constants. (C) 2004 Elsevier Ltd. All rights reserved Daha fazlası Daha az

Orhan, Umut | Hekim, Mahmut | Özer, Mahmut

Makale | 2011 | Expert Systems with Applications38 ( 10 ) , pp.13475 - 13481

We introduced a multilayer perceptron neural network (MLPNN) based classification model as a diagnostic decision support mechanism in the epilepsy treatment. EEG signals were decomposed into frequency sub-bands using discrete wavelet transform (DWT). The wavelet coefficients were clustered using the K-means algorithm for each frequency sub-band. The probability distributions were computed according to distribution of wavelet coefficients to the clusters, and then used as inputs to the MLPNN model. We conducted five different experiments to evaluate the performance of the proposed model in the classifications of different mixtures of . . . healthy segments, epileptic seizure free segments and epileptic seizure segments. We showed that the proposed model resulted in satisfactory classification accuracy rates. © 2010 Elsevier Ltd. All rights reserved Daha fazlası Daha az

Özer, Mahmut | Perc, Matjaž | Uzuntarla, Muhammet

Makale | 2009 | EPL86 ( 4 ) , pp.13475 - 13481

We investigate the regularity of spontaneous spiking activity on Newman-Watts small-world networks consisting of biophysically realistic Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise and fraction of blocked voltage-gated sodium and potassium ion channels embedded in neuronal membranes. We show that there exists an optimal fraction of shortcut links between physically distant neurons, as well as an optimal intensity of intrinsic noise, which warrant an optimally ordered spontaneous spiking activity. This doubly coherence resonance-like phenomenon depends significantly on, and can be controlled via, the fraction o . . .f closed sodium and potassium ion channels, whereby the impacts can be understood via the analysis of the firing rate function as well as the deterministic system dynamics. Potential biological implications of our findings for information propagation across neural networks are also discussed. © EPLA, 2009 Daha fazlası Daha az

Özer, Mahmut

Makale | 2004 | Iranian Journal of Science and Technology, Transaction B: Engineering28 ( 3 B ) , pp.351 - 358

In this study, the time-course of the recovery from inactivation of molluscan ionic currents is examined. Molluscan voltage-gated ionic currents are described in Hodgkin-Huxley-like equations. The peak value function of the recovering conductance is derived from the mathematical equivalent of an experimental procedure of the recovery process in a general form by including the number of inactivation gates. Then the curves of the recovery and its approximation for the molluscan ionic currents are obtained. It is shown that recovering conductance of molluscan ionic currents is asymptotically exponential. © Shiraz University.

Yılmaz, Ergin | Uzuntarla, Muhammet | Özer, Mahmut | Perc, Matjaž

Makale | 2013 | Physica A: Statistical Mechanics and its Applications392 ( 22 ) , pp.5735 - 5741

We study the phenomenon of stochastic resonance in a system of coupled neurons that are globally excited by a weak periodic input signal. We make the realistic assumption that the chemical and electrical synapses interact in the same neuronal network, hence constituting a hybrid network. By considering a hybrid coupling scheme embedded in the scale-free topology, we show that the electrical synapses are more efficient than chemical synapses in promoting the best correlation between the weak input signal and the response of the system. We also demonstrate that the average degree of neurons within the hybrid scale-free network signifi . . .cantly influences the optimal amount of noise for the occurrence of stochastic resonance, indicating that there also exists an optimal topology for the amplification of the response to the weak input signal. Lastly, we verify that the presented results are robust to variations of the system size. © 2013 Elsevier B.V. All rights reserved Daha fazlası Daha az

İşler, Yalçın | Narin, Ali | Özer, Mahmut

Makale | 2015 | Measurement Science Review15 ( 4 ) , pp.196 - 201

Congestive heart failure (CHF) occurs when the heart is unable to provide sufficient pump action to maintain blood flow to meet the needs of the body. Early diagnosis is important since the mortality rate of the patients with CHF is very high. There are different validation methods to measure performances of classifier algorithms designed for this purpose. In this study, k-fold and leave-one-out cross-validation methods were tested for performance measures of five distinct classifiers in the diagnosis of the patients with CHF. Each algorithm was run 100 times and the average and the standard deviation of classifier performances were . . . recorded. As a result, it was observed that average performance was enhanced and the variability of performances was decreased when the number of data sections used in the cross-validation method was increased. © by Yalcin Isler 2015 Daha fazlası Daha az

Yılmaz, Ergin | Özer, Mahmut

Makale | 2013 | Physics Letters, Section A: General, Atomic and Solid State Physics377 ( 18 ) , pp.1301 - 1307

We consider a scale-free network of stochastic HH neurons driven by a subthreshold periodic stimulus and investigate how the collective spiking regularity or the collective temporal coherence changes with the stimulus frequency, the intrinsic noise (or the cell size), the network average degree and the coupling strength. We show that the best temporal coherence is obtained for a certain level of the intrinsic noise when the frequencies of the external stimulus and the subthreshold oscillations of the network elements match. We also find that the collective regularity exhibits a resonance-like behavior depending on both the coupling . . .strength and the network average degree at the optimal values of the stimulus frequency and the cell size, indicating that the best temporal coherence also requires an optimal coupling strength and an optimal average degree of the connectivity. © 2013 Elsevier B.V Daha fazlası Daha az

Uzun, Rukiye | Özer, Mahmut | Perc, Matjaž

Makale | 2014 | EPL105 ( 6 ) , pp.1301 - 1307

First-spike latency following stimulus onset is of significant physiological relevance. Neurons transmit information about their inputs by transforming them into spike trains, and the timing of these spike trains is in turn crucial for effectively encoding that information. Random processes and uncertainty that underly neuronal dynamics have been shown to prolong the time towards the first response in a phenomenon dubbed noise-delayed decay. Here we study whether Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise might have shorter response times to external stimuli just above threshold if placed on a scale-free netw . . .ork. We show that the heterogeneity of the interaction network may indeed eradicate slow responsiveness, but only if the coupling between individual neurons is sufficiently strong. Increasing the average degree also favors a fast response, but it is less effective than increasing the coupling strength. We also show that noise-delayed decay can be offset further by adjusting the frequency of the external signal, as well as by blocking a fraction of voltage-gated sodium or potassium ion channels. For certain conditions, we observe a double peak in the response time depending on the intensity of intrinsic noise, indicating competition between local and global effects on the neuronal dynamics. © Copyright EPLA, 2014 Daha fazlası Daha az

Erkaymaz, Okan | Özer, Mahmut

Makale | 2016 | Chaos, Solitons and Fractals83 , pp.178 - 185

Artificial intelligent systems have been widely used for diagnosis of diseases. Due to their importance, new approaches are attempted consistently to increase the performance of these systems. In this study, we introduce a new approach for diagnosis of diabetes based on the Small-World Feed Forward Artificial Neural Network (SW- FFANN). We construct the small-world network by following the Watts-Strogatz approach, and use this architecture for classifying the diabetes, and compare its performance with that of the regular or the conventional FFANN. We show that the classification performance of the SW-FFANN is better than that of the . . . conventional FFANN. The SW-FFANN approach also results in both the highest output correlation and the best output error parameters. We also perform the accuracy analysis and show that SW-FFANN approach exhibits the highest classifier performance. © 2015 Elsevier Ltd. All rights reserved Daha fazlası Daha az

Erkan, Yasemin | Saraç, Zehra | Yılmaz, Ergin

Makale | 2019 | Nonlinear Dynamics95 ( 4 ) , pp.3411 - 3421

By virtue of recent developments in brain measurement technology, it is now recognized that information processing in brain includes not only neurons but also astrocytes. For this reason, to illustrate the effects of astrocyte on information processing in neuronal systems, we research the weak signal detection performance of the Hodgkin–Huxley neuron under the effect of astrocyte. It is found that the weak signal detection performance of the neuron exhibits the stochastic resonance phenomenon depending on noise intensity, where the presence of astrocyte with an optimal coupling strength significantly increases the detection performa . . .nce of the neuron when compared the one without astrocyte. The obtained results also reveal that there is an optimal weak signal frequency ensuring the best detection performance. Besides, we show that the colored noise exhibits a better performance than white Gaussian noise on improving the weak signal detection capacity of the neuron; moreover, the weak signal detection performance of the neuron demonstrates a resonance-like dependence on the correlation time of the noise. Finally, we investigate the effects of calcium channel noise. Although the calcium channel noise generally reduces the weak signal detection performance of the neuron, the optimal coupling strength warranting the best detection performance critically depends on its intensity. © 2019, Springer Nature B.V Daha fazlası Daha az